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Mid-level generalist Data Engineer role, metro and broad Azure skillset increases applicant competition.
Core data engineering skills transfer across industries, though Microsoft Azure/Power BI focus slightly narrows fit.
Explicit 2–4 year requirement and mandatory Microsoft/Azure tech stack but no strict certifications required.
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Design, develop, and maintain data pipelines using Microsoft Azure data services including Azure Data Factory, Azure Data Lake, and Azure SQL Database.
Build and optimize ETL/ELT processes and SQL queries to support analytics, reporting, and data warehouse implementations.
Collaborate with data analysts and business teams to deliver secure, scalable, and reliable data solutions with performance monitoring and troubleshooting.
2–4 years of experience in data engineering, database development, ETL development, or data warehousing projects.
Hands-on experience with Microsoft Azure data services and SQL Server including T-SQL, stored procedures, and query optimization.
Bachelor’s degree in Computer Science, IT, Engineering, Data Science, or related discipline.
Work Experience Required: 2–4 years in relevant field.
Experienced in building scalable data solutions on Microsoft technology stack with strong practical knowledge of Azure Data Factory and SQL development.
Familiar with data warehousing concepts such as dimensional modeling, star schema, and incremental data loads.
Capable of translating business requirements into technical data pipelines and collaborating effectively with cross-functional teams in Agile environments.